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Título: | An interactive hybrid system for identifying and filtering unsolicited email |
Autor: | Castillo Sobrino, María Dolores del; Serrano Moreno, José Ignacio | Palabras clave: | e-mail classification Heuristic knowledge Machine learning |
Fecha de publicación: | sep-2005 | Editor: | Institute of Electrical and Electronics Engineers | Citación: | Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on , vol., no., pp. 814- 815 | Resumen: | This paper presents a system for automatically detecting and filtering unsolicited electronic messages. The underlying filtering method is based on email origin and content. A heuristic knowledge base formed by spam words is extracted from labelled emails by a finite state automata. The processing of three parts of every email by a single Bayesian filter and the integration of the every part classification allows to achieve a maximum performance goal. The system is dynamic and interactive and evolves from the evolution of spam by incremental machine learning. | Versión del editor: | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1517964&isnumber=32502 | URI: | http://hdl.handle.net/10261/21688 | DOI: | 10.1109/WI.2005.31 |
Aparece en las colecciones: | (IAI) Comunicaciones congresos |
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an-interactive.pdf | 185,36 kB | Adobe PDF | Visualizar/Abrir |
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